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检索条件"机构=School of Electrical and Computer Engineering Center for Signal and Image Processing"
412 条 记 录,以下是21-30 订阅
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Unsupervised estimation of the human vocal tract length over sentence level utterances  25
Unsupervised estimation of the human vocal tract length over...
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25th IEEE International Conference on Acoustics, Speech, and signal processing, ICASSP 2000
作者: Necioǧlu, Burhan F. Clements, Mark A. Barnwell, Thomas P. Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States
This paper describes a method for the unsupervised and gender-independent estimation of the average human vocal tract length from the speech waveform, and reports results obtained on Fant's (1960) X-ray vowel data... 详细信息
来源: 评论
Self-supervised model-informed deep learning for low-SNR SS-OCT domain transformation
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Scientific Reports 2025年 第1期15卷 1-20页
作者: Sajed Rakhshani Mahnoosh Tajmirriahi Farnaz Sedighin Hossein Rabbani Amirali Arbab Aref Habibi Mohsen Pourazizi Medical Image and Signal Processing Research Center School of Advanced Technologies in Medicine Isfahan University of Medical Sciences Isfahan Iran Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan Iran Department of Ophthalmology Isfahan Eye Research Center Isfahan University of Medical Sciences Isfahan Iran
This article introduces a novel deep-learning based framework, Super-resolution/Denoising network (SDNet), for simultaneous denoising and super-resolution of swept-source optical coherence tomography (SS-OCT) images. ... 详细信息
来源: 评论
Deep Learning-Enabled, Computed Tomography-Based Race- and Sex-Specific Epicardial Adipose Tissue Thresholds for Cardiovascular Risk Stratification
Deep Learning-Enabled, Computed Tomography-Based Race- and S...
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Medical Imaging 2025: Clinical and Biomedical Imaging
作者: Buchwald, Mikolaj Shanbhag, Aakash Miller, Robert J.H. Zhang, Wenhao Michalowska, Anna M. Killekar, Aditya Lemley, Mark Kavanagh, Paul B. Fujito, Hidesato Liang, Joanna X. Builoff, Valerie Knight, Stacey Einstein, Andrew J. Miller, Edward J. Feher, Atilla Sinusas, Albert J. Chareonthaitawee, Panithaya Bullock-Palmer, Renee P. Di Carli, Marcelo F. Berman, Daniel S. Dey, Damini Slomka, Piotr J. Departments of Medicine Division of Artificial Intelligence in MedicineImaging and Biomedical Sciences Cedars-Sinai Medical Center Los AngelesCA United States Poznan Supercomputing and Networking Center Polish Academy of Sciences Poznan Poland Signal and Image Processing Institute Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los AngelesCA United States Department of Cardiac Sciences University of Calgary CalgaryAB Canada Center of Radiological Diagnostics National Medical Institute The Ministry of the Interior and Administration Warsaw Poland Department of Cardiology Nihon University Itabashi Hospital Tokyo Japan Intermountain Medical Center Heart Institute MurrayUT United States Division of Cardiology Columbia University Irving Medical Center New York CityNY United States Section of Cardiovascular Medicine Department of Internal Medicine Yale University School of Medicine New HavenCT United States Department of Cardiovascular Medicine Mayo Clinic RochesterMN United States Department of Cardiology Deborah Heart and Lung Center Browns MillsNJ United States Division of Cardiovascular Medicine Department of Medicine Brigham and Women’s Hospital Harvard Medical School BostonMA United States Cardiovascular Imaging Program Departments of Radiology and Medicine Division of Nuclear Medicine and Molecular Imaging Department of Radiology Brigham and Women’s Hospital Harvard Medical School BostonMA United States
While the volume of epicardial adipose tissue (EAT) has been linked to various conditions and showed a prognostic value of cardiovascular events, an insufficient effort was put into proposing clear, race- and sex-spec... 详细信息
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Temporal partition particle filtering for multiuser detectors with mutually orthogonal sequences
Temporal partition particle filtering for multiuser detector...
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2005 IEEE International Conference on Acoustics, Speech, and signal processing, ICASSP '05
作者: Özgür, Soner Williams, Douglas B. Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA 30332-0250 United States
We propose a blind multiuser detector based on Monte Carlo Markov chain (MCMC) techniques. The detector exploits mutually orthogonal complementary sequences to distinguish between transmitting users and space-time cod... 详细信息
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MIMO transmission subspace tracking with low rate feedback
MIMO transmission subspace tracking with low rate feedback
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2005 IEEE International Conference on Acoustics, Speech, and signal processing, ICASSP '05
作者: Yang, Jingnong Williams, Douglas B. Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA 30332-0250 United States
This paper describes a low-rate feedback algorithm for conveying partial channel state information - specifically, the dominant row subspace of the channel matrix - from the receiver to the transmitter in a continuous... 详细信息
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A ROBUST APPROACH FOR HIGH-RESOLUTION FREQUENCY ESTIMATION
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IEEE TRANSACTIONS ON signal processing 1991年 第3期39卷 627-643页
作者: SANG, GO KASHYAP, RL School of Electrical Engineering Purdue University West Lafayette IN USA Signal Processing Branch Computer Science Center Texas Instruments Inc. Dallas TX USA
We investigate a robust estimation method for estimating frequencies of received signals. The received signals can be represented as a sum of sinusoidal signals and an additive noise process. The additive noise is ass... 详细信息
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Ultra low bit rate speech coding using an ergodic hidden Markov model
Ultra low bit rate speech coding using an ergodic hidden Mar...
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2005 IEEE International Conference on Acoustics, Speech, and signal processing, ICASSP '05
作者: Lee, Matthew E. Durey, Adriane Swalm Moore, Elliot Clements, Mark Georgia Institute of Technology Center for Signal and Image Processing School of Electrical and Computer Engineering Atlanta GA 30332-0250 United States
This paper presents the framework for an ultra low bit rate speech vocoder. The system is based on a recognition-synthesis paradigm in which a single ergodic hidden Markov model (EHMM) is used to capture the statistic... 详细信息
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Near field imaging of subsurface targets using wide-band multi-static RELAX/CLEAN algorithms
Near field imaging of subsurface targets using wide-band mul...
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2005 IEEE International Conference on Acoustics, Speech, and signal processing, ICASSP '05
作者: Alam, Mubashir McClellan, James H. Center of Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA 30332-0250 United States
This paper presents two new imaging algorithms for detecting the positions of subsurface targets, e.g., land mines, using seismic waves. They are based on the CLEAN algorithm and its high resolution version RELAX. Thi... 详细信息
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Synchronous and asynchronous distributed DSP education  14
Synchronous and asynchronous distributed DSP education
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14th International Conference on Digital signal processing, DSP 2002
作者: Hayes, Monson H. Jackson, JoeI R. Center for Signal and Image Processing Georgia Institute of Technology School of Electrical and Computer Engineering AtlantaGA30332-0250 United States
The Georgia Tech Regional engineering Program (GTREP) was originally created to provide the opportunity for students in southeastern Georgia to earn a Georgia Tech undergraduate engineering degree without leaving the ... 详细信息
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Hierarchical and Multimodal Data for Daily Activity Understanding
arXiv
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arXiv 2025年
作者: Kaviani, Ghazal Yarici, Yavuz Kim, Seulgi Prabhushankar, Mohit AlRegib, Ghassan Solh, Mashhour Patil, Ameya OLIVES Center for Signal and Information Processing CSIP School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA United States Amazon Lab126 San FranciscoCA United States
Daily Activity Recordings for artificial intelligence (DARai, pronounced /Dahr-ree/), is a multimodal, hierarchically annotated dataset constructed to understand human activities in real-world settings. DARai consists... 详细信息
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